Manual wheelchair-skills courses (“bootcamps”) for wheelchair service providers: an observational study on learners’ satisfaction and perceived effectiveness
Bibliographic record
Abstract
PURPOSE: Our primary objective was to assess wheelchair service providers' opinions on manual wheelchair-skills courses ("bootcamps"). Our secondary objective was to test the hypothesis that these courses enhance the learners' self-reported capacity and confidence. MATERIALS AND METHODS: This was an observational study that took place in rehabilitation and conference centers on 407 wheelchair service providers each of whom took part in one of 26 practical workshops on manual wheelchair skills at least 1 day in duration. Post-course, all participants completed a Course Evaluation Form with ordinal (1-5), categorical, and free-response questions. A subset of 103 participants also completed a modified Wheelchair Skills Test Questionnaire (WST-Q) of "capacity" and "confidence". RESULTS: The percentages of participants who answered 5 ("extremely so") to the questions "useful?", "relevant?", "well-tolerated?", "understandable?", and "enjoyable?" were 94.1, 90.4, 92.6, 95.6, and 97.3%. The median for the Overall Satisfaction Score (OSS) (1-5) of the 26 bootcamps was 4.96. Most participants (87.1%) considered the course "just right" in duration, and (100%) stated that they would recommend the Course to others. There were numerous qualitative comments about the course content, as well as what participants found most and least useful. Over half of the WST-Q respondents reported improvements in capacity and confidence in 26 (90.0%) and 25 (86.2%) of individual skills. CONCLUSIONS: Although there is room for improvement, wheelchair service providers were generally positive about in-person courses, and the courses enhance wheelchair-skills capacity and confidence.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".